Image analysis – Image compression or coding – Quantization
Reexamination Certificate
1999-03-25
2003-03-18
Wu, Jingge (Department: 2623)
Image analysis
Image compression or coding
Quantization
C382S240000, C382S248000
Reexamination Certificate
active
06535647
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention pertains to image processing and more particularly to a method for compressing hyperspectral imagery.
In recent years, there has been increased interest in the field of remote sensing to perform precise recording of sensed energy in a number of narrow wavelength slices. Since various surface materials of interest have absorption features that are only 20 to 40 nm wide, the ability to discriminate among such features on the Earth's surface requires sensors with very high spatial, spectral, and radiometric sensitivity.
The next generation of satellite-based imaging systems will be capable of sensing scene radiation in hundreds of distinct wavelength regions. The High-Resolution Imaging Spectrometer (HIRIS), is an example of future high-resolution multi-band spectrometers. HIRIS can collect 192 spectral bands in the 0.4 to 2.5 &mgr;m wavelength region, with each band being on the order of 1000×1000 pixels. Combining these parameters with a radiometric sensitivity of 12 bits would produce a single hyperspectral image which comprises several hundred megabytes of digital information.
HIRIS is exemplary of the characteristics of future fine-spectral-resolution image sensors. The volume of data in such images requires fundamental rethinking of many image processing operations that have been developed for panchromatic and even low-dimensional multispectral data. A property of fine-spectral-resolution imagery is interband correlation. It is easy to observe in even coarse-band imagery, such as Landsat multispectral or three-primary color images, that many features of edge definition, contrast, texture, gray-level, etc., remain substantially the same from spectral band to spectral band. The interband correlation facilitates substantial reduction of the data required for storing and/or transmitting such imagery.
However, a careless approach to reducing the correlation could lead to disastrous loss of the information differences between bands that are the critical value of multispectral imagery. An improper reduction of correlation redundancy could make it impossible to exploit the imagery for significant utility.
Accordingly, it would be desirable to have a method for compressing hyperspectral imagery for storage and transmission.
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General Dynamics Decision Systems, Inc.
Jenner & Block LLC
Wu Jingge
LandOfFree
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